BTLLasso: Modelling Heterogeneity in Paired Comparison Data

Performs 'BTLLasso' (Schauberger and Tutz, 2017: Subject-Specific Modelling of Paired Comparison Data - a Lasso-Type Penalty Approach), a method to include different types of variables in paired
comparison models and, therefore, to allow for heterogeneity between subjects. Variables can be subject-specific, object-specific and subject-object-specific and
can have an influence on the attractiveness/strength of the objects. Suitable L1 penalty terms are used
to cluster certain effects and to reduce the complexity of the models.